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A two-phase maximum-likelihood sequence estimation for receivers with partial CSI
KTH, School of Electrical Engineering (EES), Communication Theory.
KTH, School of Electrical Engineering (EES), Communication Theory.ORCID iD: 0000-0002-7926-5081
KTH, School of Electrical Engineering (EES), Communication Theory.ORCID iD: 0000-0002-5407-0835
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2013 (English)In: 9th International Conference on Information, Communications and Signal Processing, ICICS 2013, IEEE Computer Society, 2013, 6782818- p.Conference paper, Published paper (Refereed)
Abstract [en]

The optimality of the conventional maximum-likelihood sequence estimation (MLSE), also known as the Viterbi Algorithm (VA), relies on the assumption that the receiver has perfect knowledge of the channel coefficients or channel state information (CSI). However, in practical situations that fail the assumption, the MLSE method becomes suboptimal and then exhaustive checking is the only way to obtain the ML sequence. At this background, considering directly the ML criterion for partial CSI, we propose a two-phase low-complexity MLSE algorithm, in which the first phase performs the conventional MLSE algorithm in order to retain necessary information for the backward VA performed in the second phase. Simulations show that when the training sequence is moderately long in comparison with the entire data block such as 1/3 of the block, the proposed two-phase MLSE can approach the performance of the optimal exhaustive checking. In a normal case, where the training sequence consumes only 0.14 of the bandwidth, our proposed method still outperforms evidently the conventional MLSE.

Place, publisher, year, edition, pages
IEEE Computer Society, 2013. 6782818- p.
Keyword [en]
Algorithms, Optimization, Channel coefficient, Data blocks, Maximum-likelihood sequence estimation, Optimality, Partial CSI, Second phase, Training sequences, Channel state information
National Category
Communication Systems
Identifiers
URN: urn:nbn:se:kth:diva-147290DOI: 10.1109/ICICS.2013.6782818ISI: 000353339000049Scopus ID: 2-s2.0-84899052292ISBN: 978-1-4799-0433-4 (print)OAI: oai:DiVA.org:kth-147290DiVA: diva2:737500
Conference
9th International Conference on Information, Communications and Signal Processing, ICICS 2013; Tainan; Taiwan; 10 December 2013 through 13 December 2013
Note

QC 20140813

Available from: 2014-08-13 Created: 2014-06-25 Last updated: 2015-12-09Bibliographically approved

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Skoglund, MikaelMing, Xiao

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  • apa
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